RT Journal Article
SR Electronic
T1 Evaluation of mouse behavioral responses to nutritive versus nonnutritive sugar using a deep learning-based 3D real-time pose estimation system
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 2022.09.19.508605
DO 10.1101/2022.09.19.508605
A1 Jineun Kim
A1 Dae-gun Kim
A1 Wongyo Jung
A1 Greg S. B. Suh
YR 2022
UL http://biorxiv.org/content/early/2022/09/19/2022.09.19.508605.abstract
AB Animals are able to detect the nutritional content of sugar independently of taste. When given a choice between nutritive sugar and nonnutritive sugar, animals develop a preference for nutritive sugar over nonnutritive sugar during a period of food deprivation1-5. To quantify behavioral features during an episode of licking nutritive versus nonnutritive sugar, we implemented a multi-vision, deep learning-based 3D pose estimation system, termed the AI Vision Analysis for Three-dimensional Action in Real-Time (AVATAR)6. Using this method, we found that mice exhibit significantly different approach behavioral responses toward nutritive sugar versus nonnutritive sugar even before licking a sugar solution. Notably, the behavioral sequences during approach toward nutritive versus nonnutritive sugar became significantly different over time. These results suggest that the nutritional value of sugar not only promotes its consumption, but also elicits distinct repertoires of feeding behavior in deprived mice.Competing Interest StatementThe authors declare the following competing interests: D-G Kim is a co-founder of the company ACTNOVA. The other authors declare no competing interests.